Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data

Vanessa Sousa da Silva; Carlos Alberto Silva; Midhun Mohan; Adrián Cardil; Franciel Eduardo Rex; Gabrielle Hambrecht Loureiro; Danilo Roberti Alves de Almeida; Eben North Broadbent; Eric Bastos Gorgens; Ana Paula Dalla Corte; Emanuel Araújo Silva; Rubén Valbuena; Carine Klauberg

doi:10.3390/rs12091438

Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data

Vanessa Sousa da Silva
, Carlos Alberto Silva
, Midhun Mohan
, Adrián Cardil
, Franciel Eduardo Rex
, Gabrielle Hambrecht Loureiro
, Danilo Roberti Alves de Almeida
, Eben North Broadbent
, Eric Bastos Gorgens
, Ana Paula Dalla Corte
, Emanuel Araújo Silva
, Rubén Valbuena
, Carine Klauberg

School of Environmental & Natural Sciences

University of California, Berkeley
Parque Tecnológico de León
Federal University of Paraná
University of Sao Paulo
University of Florida
Federal University of Jequitinhonha and Mucuri Valleys
Federal Rural University of Pernambuco
University of Maryland

Research output: Contribution to journal › Article › peer-review

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Original language	English
Journal	Remote Sensing
Volume	12
Issue number	9
DOIs	https://doi.org/10.3390/rs12091438
Publication status	Published - 1 May 2020

Keywords

LiDAR
eucalyptus
forest attributes
machine learning
variable selection

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10.3390/rs12091438Licence: CC BY

remotesensing-12-01438Final published version, 4.49 MBLicence: CC BY

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Silva, V. S. D., Silva, C. A., Mohan, M., Cardil, A., Rex, F. E., Loureiro, G. H., Almeida, D. R. A. D., Broadbent, E. N., Gorgens, E. B., Dalla Corte, A. P., Silva, E. A., Valbuena, R., & Klauberg, C. (2020). Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data. Remote Sensing, 12(9). https://doi.org/10.3390/rs12091438

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title = "Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data",

keywords = "LiDAR, eucalyptus, forest attributes, machine learning, variable selection",

author = "Silva, \{Vanessa Sousa da\} and Silva, \{Carlos Alberto\} and Midhun Mohan and Adri{\'a}n Cardil and Rex, \{Franciel Eduardo\} and Loureiro, \{Gabrielle Hambrecht\} and Almeida, \{Danilo Roberti Alves de\} and Broadbent, \{Eben North\} and Gorgens, \{Eric Bastos\} and \{Dalla Corte\}, \{Ana Paula\} and Silva, \{Emanuel Ara{\'u}jo\} and Rub{\'e}n Valbuena and Carine Klauberg",

year = "2020",

month = may,

day = "1",

doi = "10.3390/rs12091438",

language = "English",

volume = "12",

journal = "Remote Sensing",

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Silva, VSD, Silva, CA, Mohan, M, Cardil, A, Rex, FE, Loureiro, GH, Almeida, DRAD, Broadbent, EN, Gorgens, EB, Dalla Corte, AP, Silva, EA, Valbuena, R & Klauberg, C 2020, 'Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data', Remote Sensing, vol. 12, no. 9. https://doi.org/10.3390/rs12091438

TY - JOUR

T1 - Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data

AU - Silva, Vanessa Sousa da

AU - Silva, Carlos Alberto

AU - Mohan, Midhun

AU - Cardil, Adrián

AU - Rex, Franciel Eduardo

AU - Loureiro, Gabrielle Hambrecht

AU - Almeida, Danilo Roberti Alves de

AU - Broadbent, Eben North

AU - Gorgens, Eric Bastos

AU - Dalla Corte, Ana Paula

AU - Silva, Emanuel Araújo

AU - Valbuena, Rubén

AU - Klauberg, Carine

PY - 2020/5/1

Y1 - 2020/5/1

KW - LiDAR

KW - eucalyptus

KW - forest attributes

KW - machine learning

KW - variable selection

U2 - 10.3390/rs12091438

DO - 10.3390/rs12091438

M3 - Article

SN - 2072-4292

VL - 12

JO - Remote Sensing

JF - Remote Sensing

IS - 9

ER -

Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data

Keywords

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